–Adaptable to a wide variety of semantic data:Facet hierarchy projection andsemantic link generation are based on extendable logic rules. The projection ruleshave been tested with three different data sets.

•The Multi-Facet Search Engine Ontogator

–Scalable to accommodate large amounts of data

–Easily integrated and extended with additional functionality

•OntoViews-C, the Interaction and Control Component

–Easily integrated and extended with additional functionality

–Able to provide its functionality also to other programs as Semantic Web Services

Semantic Computing Research Group

18

http://www.cs.helsinki.fi/group/seco/

UNIVERSITY

OF

HELSINKI

HELSINKI UNIVERSITY OF TECHNOLOGY

Implementation

•The Logic Server Ontodella

–Adaptable to a wide variety of semantic data:Facet hierarchy projection andsemantic link generation are based on extendable logic rules. The projection ruleshave been tested with three different data sets.

•The Multi-Facet Search Engine Ontogator

–Scalable to accommodate large amounts of data

–Easily integrated and extended with additional functionality

•OntoViews-C, the Interaction and Control Component

–Easily integrated and extended with additional functionality

–Able to provide its functionality also to other programs as Semantic Web Services

Semantic Computing Research Group

19

http://www.cs.helsinki.fi/group/seco/

UNIVERSITY

OF

HELSINKI

HELSINKI UNIVERSITY OF TECHNOLOGY

The Multi-Facet Search Engine Ontogator

•Is a generic view-based RDF search engine

–Defines and implements an RDF-based query interfacedefined as an OWL ontology

–Replies to queries in RDF/XML that has a fixed structure.

–The query operations are based on category and itemselectors. The functionality of the engine can be extended byimplementing new selector types (keyword search andgeolocation search in OntoViews, for example)

•Has been tested with dmoz.org data to scale to up to2.3 million items and 275.000 categories with searchtimes of about 5 seconds.

•Future work: Does not yet scale well to accommodatemultiple simultaneous users

Semantic Computing Research Group

20

http://www.cs.helsinki.fi/group/seco/

UNIVERSITY

OF

HELSINKI

HELSINKI UNIVERSITY OF TECHNOLOGY

Implementation

•The Logic Server Ontodella

–Adaptable to a wide variety of semantic data:Facet hierarchy projection andsemantic link generation are based on extendable logic rules. The projection ruleshave been tested with three different data sets.

•The Multi-Facet Search Engine Ontogator

–Scalable to accommodate large amounts of data:Ontogator has been testedwith dmoz.org data to scale to up to 2.3 million items and 275.000 categories withsearch times of about 5 seconds.

–Easily integrated and extended with additional functionality:The architectureallows for extensions by implementing new types of selectors (keyword,geolocation). The RDF query model and fixed structure RDF/XML result allow foreasy integration.

•OntoViews-C, the Interaction and Control Component

–Easily integrated and extended with additional functionality

–Able to provide its functionality also to other programs as Semantic Web Services

Semantic Computing Research Group

21

http://www.cs.helsinki.fi/group/seco/

UNIVERSITY

OF

HELSINKI

HELSINKI UNIVERSITY OF TECHNOLOGY

Implementation

•The Logic Server Ontodella

–Adaptable to a wide variety of semantic data:Facet hierarchy projection andsemantic link generation are based on extendable logic rules. The projection ruleshave been tested with three different data sets.

•The Multi-Facet Search Engine Ontogator

–Scalable to accommodate large amounts of data:Ontogator has been testedwith dmoz.org data to scale to up to 2.3 million items and 275.000 categories withsearch times of about 5 seconds.

–Easily integrated and extended with additional functionality:The architectureallows for extensions by implementing new types of selectors (keyword,geolocation). The RDF query model and fixed structure RDF/XML result allow foreasy integration.

•OntoViews-C, the Interaction and Control Component

–Easily integrated and extended with additional functionality

–Able to provide its functionality also to other programs as Semantic Web Services

Semantic Computing Research Group

22

http://www.cs.helsinki.fi/group/seco/

UNIVERSITY

OF

HELSINKI

HELSINKI UNIVERSITY OF TECHNOLOGY

The Interaction and Control Component OntoViews-C

•Built on top of the Apache Cocoon architecture

–The Cocoon architecture is based upon the concept ofpipelines, comprised of modular components (generators,transformers and serializers) that consume and/or produceXML

–This forces a modular, reusable and extendable design

•In OntoViews, all components produce not only XML,but valid RDF/XML. This, along with a generator forhandling HTTP requests, allows for the exposition ofall parts of the system as Web Services

Semantic Computing Research Group

23

http://www.cs.helsinki.fi/group/seco/

UNIVERSITY

OF

HELSINKI

HELSINKI UNIVERSITY OF TECHNOLOGY

Implementation

•The Logic Server Ontodella

–Adaptable to a wide variety of semantic data:Facet hierarchy projection andsemantic link generation are based on extendable logic rules. The projection ruleshave been tested with three different data sets.

•The Multi-Facet Search Engine Ontogator

–Scalable to accommodate large amounts of data:Ontogator has been testedwith dmoz.org data to scale to up to 2.3 million items and 275.000 categories withsearch times of about 5 seconds.

–Easily integrated and extended with additional functionality:The architectureallows for extensions by implementing new types of selectors (keyword,geolocation). The RDF query model and fixed structure RDF/XML result allow foreasy integration.

–Able to provide its functionality also to other programs as Semantic Web Services:All subparts of the system are available to be used via Web Services

Semantic Computing Research Group

24

http://www.cs.helsinki.fi/group/seco/

UNIVERSITY

OF

HELSINKI

HELSINKI UNIVERSITY OF TECHNOLOGY

Summary–

OntoViews is:

•A search engine based on the semantics of the content:Concept-based Multi-Facet andkeyword search

•Browsing functionality based on the semantic relations in the underlying knowledgebase:Classification tree view, explicit semantic links in item view

•Usable for an end-user:Based on the tested and true Flamenco interface

•Easily integrated and extended with additional functionality:Seamless integration in theuser interface of keyword and other searches, the search architecture allows for extensions,and the Cocoon control architecture forces a modular, reusable and extendable design. Allcomponents operate independently, consuming and/or producing RDF/XML.

•Usable with a variety of different devices:

Different user interfaces and functionality fordifferent devices

•Adaptable to a wide variety of semantic data:Facet hierarchy projection and semantic linkgeneration are based on extendable logic rules. The projection rules have been tested withthree different data sets.

•Scalable to accommodate large amounts of data:OntoViews has been tested withdmoz.org data to scale to up to 2.3 million items and 275.000 categories with search times ofabout 5 seconds.

•Able to provide its functionality also to other programs as Semantic Web Services:Allsubparts of the system are available to be used via Web Services